The Blacksite platform runs six connected assessments — covering AI business impact, transformation value, shadow AI exposure, data provenance, output reliability, and vendor governance. Run one assessment to answer a specific question, or run the full set for a complete operating view. Every assessment produces practical artifacts leadership can use to make decisions, approve pilots, contain risk, and brief the board.

Each assessment produces practical artifacts leadership can use to make decisions, approve pilots, control risk, and brief the board.

This assessment helps leadership understand where AI is creating business value, operational dependency, legal exposure, cyber risk, vendor risk, and decision-quality concerns.It combines business impact analysis, AI use-case discovery, AI security maturity calibration, and governance operating-model design. 

• AI business impact
• AI use-case maturity
• Adoption velocity
• Executive and board concerns
• Risk ownership and accountability
• AI security maturity
• Policy and standards readiness
• Use-case lifecycle management
• Risk acceptance and escalation
• Governance cadence and reporting

• AI Business Impact Map
• AI use-case risk tiering
• AI security maturity snapshot
• AI governance gap summary
• Target Operating Model
• Cross-functional RACI
• Board reporting model
• 30/60/90-day roadmap
• Prioritized assessment path

AI risk cannot be managed at the tool level alone. Leadership needs a clear operating model for who owns AI risk, how use cases are approved, how controls are measured, how exceptions are handled, and how exposure is reported before adoption scales across the business.

Most companies have AI activity. Far fewer have an AI investment thesis.

This assessment helps organizations identify where AI can create measurable value, quantify financial impact, evaluate process and workforce implications, and prioritize use cases based on value, feasibility, risk, and readiness. It separates AI theater from fundable transformation by connecting AI initiatives to EBITDA, operating performance, risk reduction, and governance requirements.

• Business outcome priorities
• AI use-case opportunities
• Process improvement potential
• Human capital and role impact
• Revenue and lead-generation opportunities
• Cost takeout and productivity gains
• Customer experience improvement
• Financial impact and EBITDA levers
• Readiness and feasibility
• Risk and control dependencies
• Transformation roadmap

• AI Outcome Priority Map
• AI Use Case Inventory
• Process and Workforce Impact Map
• EBITDA Bridge
• Value and Feasibility Scorecard
• Risk-Adjusted Prioritization Matrix
• Pilot Candidate List
• Governance and Control Dependency Map
• 30/60/90-Day Transformation Roadmap
• Blacksite Assessment Routing Plan

Blacksite helps leadership determine which AI initiatives are worth funding, which require controls first, which should be piloted, and which should be avoided.

The Blacksite AI Containment Assessment identifies known, likely, and technically observable AI use across the organization. It evaluates where employees may be using public AI tools, embedded AI features, meeting bots, browser extensions, coding assistants, personal accounts, or AI-enabled SaaS platforms outside formal governance. This assessment focuses on the risk created when AI adoption moves faster than security, legal, procurement, and policy controls.

• Shadow AI visibility
• Sensitive-data exposure
• Trade-secret containment gaps
• Employee use of personal AI accounts
• Approved versus unapproved AI tools
• AI use in high-risk workflows
• Policy and control maturity
• Technical detection capability
• Output verification practices
• 30/60/90-day containment priorities

• Shadow AI exposure map
• AI tool inventory
• Sensitive-data exposure matrix
• Trade-secret containment score
• Technical visibility gap analysis
• Policy and control findings
• High-risk workflow summary
• Executive-ready containment report
• Prioritized remediation roadmap

The greatest AI risk is often not malicious behavior. It is productive employees using powerful tools before the organization knows how to control them. Blacksite helps leadership understand where AI use is creating exposure and what controls are needed to contain it.

Blacksite Data Provenance Diligence evaluates whether an organization’s data sources, AI training claims, proprietary datasets, and data-use rights are traceable, lawful, secure, and defensible.

This assessment is especially valuable for investors, acquirers, AI companies, private equity firms, law firms, and enterprises that need to understand whether a claimed AI data moat is durable or simply a weak collection of scraped, synthetic, poorly governed, or insufficiently documented data.

• Data source provenance
• Ownership and usage rights
• Licensing and lawful-use evidence
• Privacy and data-protection posture
• Security controls around data assets
• Chain of custody and lineage
• Synthetic data and transformation history
• Data quality and AI readiness
• Retention, deletion, and lifecycle controls
• Vendor and third-party data dependencies
• AI moat credibility

• Dataset inventory
• Source and rights review
• Privacy and data-protection findings
• Data security control review
• Lineage and chain-of-custody assessment
• Synthetic data transparency review
• AI/data moat credibility score
• Diligence red flags
• Executive diligence memo
• Remediation roadmap

AI value depends on data quality, data rights, governance, and defensibility. A company may claim proprietary data advantage, but without provenance, lawful-use evidence, security controls, and quality assurance, that advantage may create more risk than enterprise value.

The Blacksite AI Output Reliability Review assesses whether AI-generated outputs are accurate, grounded, verified, traceable, and appropriately supervised before they affect clients, executive decisions, legal documents, cyber analysis, financial work, HR workflows, board reporting, or operational systems. This assessment addresses one of the most under-governed areas of enterprise AI adoption: trusting fluent AI output without sufficient evidence, review, or accountability.

• AI output use cases
• Business-critical reliance points
• Human review and sign-off
• Grounding and source traceability
• Accuracy and hallucination testing
• Uncertainty and confidence handling
• Role-based decision authority
• Prompt, context, and data quality
• Adversarial manipulation resistance
• Auditability and evidence retention
• Monitoring and incident response

• AI output use-case inventory
• Reliance and criticality map
• Grounding and traceability findings
• Human review gap analysis
• AI decision-authority map
• Output reliability score
• High-risk workflow findings
• Verification control recommendations
• Executive reliability report
• 30/60/90-day assurance roadmap

AI vendors test model behavior. Blacksite evaluates whether organizations can safely rely on AI outputs inside real business workflows. The model may be strong, but the workflow may still be dangerous if outputs are not reviewed, grounded, documented, or limited by appropriate human authority.

The Blacksite AI Vendor Governance Review helps organizations classify AI tools, evaluate vendor risk, and define which platforms should be approved, restricted, conditionally allowed, prohibited, or retired. This assessment supports procurement, legal, security, privacy, compliance, and business leaders responsible for managing the expanding universe of AI-enabled tools entering the enterprise.

• AI vendor inventory
• Approved, restricted, and prohibited tool status
• Third-party due diligence
• Contract and data-processing terms
• Privacy and data-protection controls
• Security assurance and technical safeguards
• Data retention and model-training terms
• API, OAuth, plugin, and agentic permissions
• Subprocessor and supply-chain risk
• Monitoring, logging, and incident response
• Renewal and decommissioning controls

• AI tool register
• Vendor tiering and risk classification
• Approved/restricted/prohibited tool recommendations
• Vendor due diligence findings
• Data retention and model-training risk review
• Integration and permission risk analysis
• Contract and DPA gap summary
• Vendor governance score
• Executive vendor risk report
• Control roadmap

Many organizations do not have a complete inventory of AI tools already in use. Others approve tools without understanding data retention, training-use rights, subprocessors, integrations, or agentic permissions.

Blacksite helps organizations decide which tools belong inside the business and under what conditions.

Blacksite is designed for organizations that need practical AI governance, risk containment, and value analysis without committing to a large enterprise platform or open-ended advisory engagement.

We support:

• Mid-market companies
• Private equity firms
• Portfolio companies
• Law firms
• Cybersecurity and MSP providers
• AI companies
• Investors and acquirers
• Boards and executive teams
• General counsel and compliance leaders
• CIOs, CISOs, and risk leaders